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Article Dans Une Revue Earth Année : 2012

Automated recognition of spikes in 1 Hz data recorded at the Easter Island magnetic observatory

Anatoly Soloviev
  • Fonction : Auteur
Shamil Bogoutdinov
  • Fonction : Auteur
Alexei Gvishiani
  • Fonction : Auteur
Sergey Agayan
  • Fonction : Auteur
Aline Peltier
Benoit Heumez

Résumé

In the present paper we apply a recently developed pattern recognition algorithm SPs to the problem of automated detection of artificial disturbances in one-second magnetic observatory data. The SPs algorithm relies on the theory of discrete mathematical analysis, which has been developed by some of the authors for more than 10 years. It continues the authors' research in the morphological analysis of time series using fuzzy logic techniques. We show that, after a learning phase, this algorithm is able to recognize artificial spikes uniformly with low probabilities of target miss and false alarm. In particular, a 94% spike recognition rate and a 6% false alarm rate were achieved as a result of the algorithm application to raw one-second data acquired at the Easter Island magnetic observatory. This capability is critical and opens the possibility to use the SPs algorithm in an operational environment.

Dates et versions

insu-03583026 , version 1 (21-02-2022)

Identifiants

Citer

Anatoly Soloviev, Arnaud Chulliat, Shamil Bogoutdinov, Alexei Gvishiani, Sergey Agayan, et al.. Automated recognition of spikes in 1 Hz data recorded at the Easter Island magnetic observatory. Earth, 2012, 64, pp.743-752. ⟨10.5047/eps.2012.03.004⟩. ⟨insu-03583026⟩
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